Technically Speaking, January 2014

LETTER FROM THE EDITOR

This month’s newsletter begins with an article that covers the past and the present. Ralph Acampora, CMT, was present at the beginning of the MTA and has been a part of every major development in the organization during the past 40 years. He looks forward to the next 40 years of the MTA and expects much to change over that time. However, he also expects some things to remain as they are. Ralph, like so many others, expects the MTA to continue to be a professional organization where ideas are freely shared. The MTA will continue advancing the profession of technical analysis on Wall Street.

In addition to taking a long-term look into the future, we are also looking just a few months ahead in this issue. Although it is only January, the planning for this year’s Annual Symposium is well underway. In this month’s issue of Technically Speaking we are offering insights from two of the scheduled speakers, Perry Kaufman and John Murphy, CMT.

We hope that you will be planning to attend the Symposium and to participate in your local MTA Chapter in the coming year. We also hope you will share your work through the newsletter. Submissions can be sent at any time to editor@mta.org.

Michael Carr

What's Inside...

LOOKING BACK AND LOOKING AHEAD: A CONVERSATION WITH RALPH ACAMPORA, CMT

Amber Hestla-Barnhart

In late-December, I had the chance to speak with Ralph Acampora, CMT, about the early days of the MTA, the...

THE STOCK AND THE COMPANY

Ralph Acampora, CMT

Editor’s note: This article originally appeared in the May 1982 MTA Journal, issue 13. It is still timely and offers...

TRADING PHILOSOPHY AND STRATEGY OVERVIEW

Perry J. Kaufman

Editor’s note: This article was published at KaufmanSignals.com and is reprinted here worth permission of the author.

Understanding Systems and...

INTERMARKET ANALYSIS

Arthur Hill, CMT

Editor’s note: This article originally appeared at StockCharts.com and is republished here with permission.

Introduction

Intermarket analysis is a branch...

INTEREST RATES AND STOCK PRICES

Stan Lipstadt

Editor’s note: Stan Lipstadt, Vice President of the MTA in 1976-1977, and Vice President for seminars for the MTA on...

LONG-TERM ELLIOT WAVE ANALYSIS OF GOLD

Lara Iriarte, CMT

Editor’s note: This article is presented as an example of a comprehensive approach to Elliott Wave analysis.

Main...

A FORECAST FOR THE NIFTY

Purab Shah

The Nifty is a benchmark index for the stock market in India. This...

CHART OF THE MONTH

stockcharts.com

LOOKING BACK AND LOOKING AHEAD: A CONVERSATION WITH RALPH ACAMPORA, CMT

In late-December, I had the chance to speak with Ralph Acampora, CMT, about the early days of the MTA, the organization’s growth over the past 40 years and his thoughts on where the MTA will be 40 years from now.

In the early 1970’s, a young Ralph Acampora kept running into John Brooks while running errands on Wall Street. At that time, technical analysts relied on hard copy data services and chart books. As junior analysts at the firms, Ralph and John stood in line together to pick up the books directly from the publisher. While waiting in line for the data they needed to update their point and figure charts by hand, they realized technicians were probably the only group on Wall Street without a formal society where they could exchange ideas.

The New York Society of Security Analysts (NYSSA) was the largest group of analysts. Analyst meetings were common on Wall Street at that time. Analysts were a primary source of information and the meetings were an opportunity to share research and to hear from companies that courted the analysts. Many of the analysts met regularly to discuss the important aspects of their specific industry, e.g. auto analysts, chemical analysts, etc.

While the NYSSA meetings provided valuable information for both analysts and the companies they covered, they didn’t offer a lot of information that would help technicians. The NYSSA is dedicated to fundamental analysis and technical analysts use price data rather than financial statements to reach their conclusions. Company presentations would be interesting, they would not help Ralph or other technicians complete their research.

Another reason the NYSSA and other societies were not as valuable to technical analysts is because technical analysts, just as they do now, covered the broad market rather than specializing in a sector. There was no society of technical analysts but Ralph and John realized technicians could benefit from an exchange of ideas. Together with Bob Farrell (Merrill Lynch) and Alan Shaw (Harris, Upham & Co.) and 14 other professional technical analysts, they formed the Market Technicians Association which was formally incorporated in 1973 as the Market Technicians Association of New York Inc. (In 1996, the name was formally changed to the Market Technicians Association to reflect the growing international membership.)

Education Was a Primary Goal

MTA meetings provided an opportunity for members to share their work in a professional atmosphere. From the beginning, the focus has been on ideas rather stock tips. As Ralph explained to me, at those first meetings, members shared the same competitive spirit and their new indicators and everyone was friendly and professional. The cross flow of ideas helped them all to become better analysts.

To ensure the success of the MTA, Ralph sought the advice of some of the old timers on Wall Street: Bob Farrell (Merrill, Lynch), Alan Shaw (Harris, Upham & Co), Ken Ward, Hayden Stone & Co.) and John Schultz (Frobes Magazine). At the time, Ken Ward was one of the oldest living technicians at the time and had survived Crash of 1929 and the Great Depression.

The old timers were skeptical at first. They insisted that this new organization be the utmost in ‘professionalism” – they knew that the MTA would initially have a credibility hurdle with many of the Street. Increasing the credibility of technical analysis would be a difficult task but this prestigious group agreed to help as long as the organization was professional.

To increase the credibility of the MTA, membership was restricted to the analysts who were most likely to be taken seriously by Wall Street. At first, this was a small group. The MTA constitution only allowed analysts who prepared technical reports for portfolio managers at investment management firms or stock market letter writers who provided research to clients to join. At first, there were only 18 members. As the organization became more diverse, the constitution was updated and as Ralph said, the evolution of the MTA memberships has been “beautiful” to watch and be a part of.

Ralph at this time was a relative newcomer to the industry, having started working on Wall Street in 1964; about 40 years after Mr. Ward entered the business. At the first MTA meeting, Ralph realized the MTA would provide a unique opportunity for young analysts like him to learn from experience. He asked Mr. Ward what the most difficult market he had ever experienced had been and then answered his own question with “of course, it was the Crash of 1929.” Mr. Ward answered, “No, kid, that was a layup. The toughest market I ever saw, by far, was the one from 1962 to 1966. If you go through something like that, it will be the roughest thing you’ll ever experience.”

This answer was surprising. Ralph knew the market had gone up over that time.

Mr. Ward explained, “It went up and up and up and rolled right over all of us, bulls and bears alike. Nobody believed it. And it made us look like fools.”

Ralph did go through something like that in the 1990’s and again last year. He has remembered Mr. Ward’s advice and he follows the market rather than trying to predict it. This approach to the markets has been successful for Ralph personally and the credibility has increased over the years.

Public Acceptance of Technical Analysis Came From Success

When I interviewed Ralph, he did not tell me about his personal success but he did mention that technical analysis has become accepted in the media, especially on CNBC. He also failed to mention how he personally sparked a market selloff, a story I remember from the book Beyond Greed and Fear: Understanding Behavioral Finance and the Psychology of Investing by Hersh
Shefrin.

In discussing technical analysis, Shefrin recounts how Ralph Acampora made an amazingly accurate market call in 1998 and was blamed by many for single-handedly causing a market crash in August of that year.

During that time, Ralph was the widely respected and followed technician for Prudential Securities. Ralph recalls that he had been travelling on a camera safari that July, and when he got back, CNBC anchor Ron Insana called to schedule a short interview. On August 3, 1998, Ralph told the audience that he was starting to see signs of deterioration in the bull market. He was concerned about breadth indicators, long a favorite gauge of sentiment and the health of a market move in his analysis.

That night, while completing an in-depth review of the market, Ralph became deeply concerned and told his boss that he might need to make a major market call, in his words, the next day “he may have to shoot the bull, his best friend.”

With futures up the next morning, Ralph delayed making his call. But within an hour of the opening, he knew it was time to tell his clients that his position had changed. Negative breadth had convinced him, and Ralph noticed the traders were “big game hunting…shooting market leaders like Gillette and Proctor and Gamble.”

At 11:00 Eastern time, Ralph placed a call to the brokers throughout the Prudential system that stocks were in a cyclical bear market. This was based solely on his technical work, in particular breadth and sentiment. A few hours later, he returned to CNBC and shared his forecast with the audience.

That day, the Dow dropped 299.43 points, a very significant move at that time.

Later that month, Ralph told Newsweek, “We’ve had “stealth” corrections for the last three and a half years, but that was mostly small and midsize stocks. Now I want to drop the word “stealth.” This particular decline is starting to eat into the blue chips. We’re hitting lots of new lows every day. I’m saying, “Ooh, this is nasty.””

In hindsight, traders learned that Ralph had simply noticed that the market was discounting problems with Russian bonds and hedge fund Long Term Capital Management. The market was discounting the future bad news, and technical analysis, in the hands of an expert, was working well.

This occurred 25 years after the MTA was founded and demonstrated that technical analysts were no longer thought of as second class citizens on Wall Street. By then, people were hungry for the information that technicians provided.

Ralph had been creating and feeding that hunger the whole time. Before CNBC, there was Wall Street Week with Louis Rukeyser, a PBS show that attracted millions of viewers every Friday night. This show was the only source of financial news for some investors and viewers became acquainted with Ralph Acampora who appeared frequently on the show over 23 years. Rukeyser provided time for technicians to explain their views and even developed the “Elf Index” to track their views.

By the early 1990’s, CNBC and other financial news shows flooded the airwaves with commentary and technical analysis was receiving more and more air time. Ralph and other members of the MTA worked to educate the network personalities and their viewers and technical analysis became more and more accepted.

Professional Recognition of Technical Analysis Also Followed Success

In part, the increased credibility of technical analysis was the result of the efforts of the MTA. In particular, the CMT exam had help boost the image of technicians. The CMT exam was part of one of Ralph’s greatest accomplishments in the past 40 years.

On Friday, December 17, 2004, Ralph joined several other MTA members in a presentation to the Securities and Exchange Commission (SEC). They were making the case that the CMT exam should carry the same benefits as the CFA exam in the case of testing for analyst certifications. One of the SEC attorneys seemed to be skeptical. He held up a chart and asked Ralph to tell him one fact that was contained in the chart. Ralph was certain of the answer, “Price. Price is a fact.” The attorney said that’s the best answer I’ve ever heard and in early 2005, the CMT exam was approved as an alternative to the analysis portion of the Research Analyst Qualification Examination (Series 86).

Although there have been a number of accomplishments, the MTA has also faced challenges in its first 40 years. Each challenge was met and the organization grew stronger as a result of many of them. The MTA has grown from 18 members in New York City to more than 3,500 members around the world. The organization is now professionally managed and on track for the next 40 years.

Technical analysis will continue to evolve and expand in the next 40 years and Ralph believes that generations to come will still sit around a table together and uphold the original values of the MTA to conduct themselves professionally while sharing their work and shake hands even when they disagree.

He ended our call by noting that he loves the MTA because of the way it brings people together. He told me “you can learn so much from each other” and he looks forward to being a part of that process for years to come. He wants to spend more time meeting with new members and sharing memories with old members and Ralph takes pride in the fact that the organization will be there for his new step-grandson to find camaraderie if he decides to work in the family business one day.

A Personal Observation

In talking with Ralph, it quickly becomes obvious that he is more focused on results than personal recognition. None of his memories seemed to include solo efforts and all of his accomplishments seemed to be the result of his collaborations. I was struck by the fact that Ralph proved the “mensch effect” described by Samuel Arbesman in The Half-life of Facts: Why Everything We Know Has an Expiration Date:

There’s even research that examines how being a mensch is related to scientific productivity.

For example, in the 1960s, Harriet Zuckerman, a sociologist of science—someone who studies the interactions and people
underlying the entire scientific venture—decided to study the scientific output of Nobel laureates to see if any patterns could be seen in how they work that might distinguish them from their less successful peers.

One striking finding was the beneficence of Nobel laureates … or as Zuckerman termed it, noblesse oblige.

In general, when a scientific paper is published, the author who did the most is listed first…What she found was that Nobel laureates are first authors of numerous publications early in their careers, but quickly begin to give their junior colleagues first authorship.

And this happens far before they receive the Nobel Prize.

As one generous Nobel laureate in chemistry put it: ‘It helps a young man to be senior author, first author, and doesn’t detract from the credit that I get if my name is farther down the list.’

On the other hand, those peers of Nobel laureates who were not as successful tried to maintain first authorship for themselves far more often, garnering more glory for themselves.

By their forties, Nobel laureates are first authors on only 26% of their papers, as compared to their less accomplished
contemporaries, who are first authors 56% of the time.

Ralph was a major contributor to the MTA in its first 40 years but he is quick to mention others who also contributed. Although his name could easily be mentioned first in almost every story, he always gives credit to someone else for the inspiration or the shared effort. Ralph is also a major reason that technical analysis is widely accepted among individual and institutional investors today. He has been explaining how technical analysis works for fifty years and providing proof that it works in real time with accurate and actionable advice that helps people make money. When I spoke to him, he failed to mention how he personally has been one of the leading proponents of technical analysis for decades.

In my recent conversation with Ralph, I expected to hear how he did so much in his life but every story included the name of at least one other person who was a part of the effort. Although being a mensch is not a requirement of MTA membership, it is a common trait among the most successful members and Ralph demonstrates that it is possible to be humble and extraordinarily successful. Although Ralph cited Joe DiMaggio in our phone call, his career brings to mind another baseball legend that spent a great deal of time in New York. Ralph has proven that Leo Durocher was wrong when he said “nice guys finish last.” Ralph is at the top of his profession because he is a nice guy.

Ralph Acampora, CMT, is Senior Managing Director, Altaira Ltd. Ralph is a pioneer in the development of market analytics and has a global reputation as a market historian and a technical analyst. He is the former Director of Technical Research at Kidder Peabody and Prudential Securities, a published author, popular lecturer and a leading international expert, consulted by prominent financial experts and journalists worldwide.

Contributor(s)

Amber Hestla-Barnhart

Bio coming soon.

THE STOCK AND THE COMPANY

Editor’s note: This article originally appeared in the May 1982 MTA Journal, issue 13. It is still timely and offers useful information for technicians almost 32 years after it was written.

One diagram says it all: For a well-rounded approach, one should integrate technical and fundamental analysis; when joined together, they create the whole picture. The perennial battle between supply and demand is what makes markets, but unfortunately there is still ferment in the investment community. Some make it their sworn duty to pit the technicians against the fundamentalists.

As moderator of the panel entitled “Integrating Technical Analysis with Other Research Disciplines,” the author of this article feels that his experience as an educator and a professional technician may provide some fresh insights into the meshing of these two investment disciplines.

As an instructor in the basic tenets of technical analysis at the New York Institute of Finance for the last 12 years, I have noticed a steady increase in interest for the subject. Through some very difficult bear markets in the past dozen years, the NYIF had to temporarily cancel some classes in various aspects of finance because of a drop in attendance. This has not happened with technical analysis classes; in fact, the student mix over the years has broadened considerably, from public attendees (including professionals such as doctors, engineers, etc. ) to investment professionals, research directors, block traders, floor traders, bond traders, option traders, portfolio managers and, more and more, fundamental analysts.

Perhaps it is the sign of the times — this past semester the NYIF had its largest enrollment for the technical-analysis class in approximately 10 years. One could take this as a negative and conclude that the technical approach is becoming too popular and will self-destruct because “everyone is doing the same thing.” Well, I’ve heard that song many times before and disagree with -the conclusion. Yes, technical analysis is receiving more than just lip service in many corners of the investment community, but we feel its recent surge in popularity is due primarily to the fact that other inputs just didn’t help in the past two years. Once the market commences that long-soughtafter major bull trend, and everyone, regardless of investment approach, is making money, the love affair for technical analysis will wane once again, simply because it will be “easy to make money in the stock market. ”
Remember the old adage: “Never confuse brains with a bull market.” It is only in times of real need that technicians are sought after; the recent market has been no exception.

The rise in popularity of technical analysis shouldn’t obscure the importance of other inputs. In fact, one should become more aware of other research disciplines simply because technical work has been so useful and so many have embraced it recently. When reflecting on the subject of investments and all that it incorporates, it only seems logical that one would want to fill his quiver with as many arrows as possible; if most of these (the technical arrow, of course, being one) hit the same target, then the evidence suggests which road to take.

As a professional technician, who has recently joined Kidder Peabody & Co Inc. and established its first formal technical department, I have encountered many pleasant experiences and some old prejudices. After being on board for a couple of months, one salesman called and admitted that he had very little use for technicians. After discussing philosophies, it really boiled down to his final statement, “I don’t dislike technicians; I just never learned anything about technical analysis while in grad school.” The biggest problem is a lack of understanding — once the mystique of technical analysis is eliminated, it is quickly assimilated into the decision making process.

The one big drawback I see in introducing technical analysis to a new audience is vocabulary. Technicians speak a foreign language: flags, pennants, etc. — you’d think we were at a parade; “head & shoulders is a dandruff shampoo… ” If you are serious about developing a working relationship with non-technicians or presenting an opinion regarding the market, groups or stocks, downplay the technical jargon. Most people are willing to listen, but honestly, they get turned off when flooded with terms
that can easily be translated into English.

Like any conflict or area of opposing opinions, both sides must communicate; once we understand each other, surprisingly we all
probably agree more often than not.

Contributor(s)

Ralph Acampora, CMT

Ralph Acampora, CMT is a pioneer in the development of market analytics. He has a global reputation as a market historian and a technical analyst, providing unique insights on market timing and related investment strategy issues to a wide audience within the...

TRADING PHILOSOPHY AND STRATEGY OVERVIEW

Editor’s note: This article was published at KaufmanSignals.com and is reprinted here worth permission of the author.

Understanding Systems and Markets

Algorithmic trading systems bring the investor good returns and increased predictability. Compared to discretionary trading it is analogous to the turtle and the hare. You can’t rush a system or make it do anything other than what it was intended for. Each strategy has a particular profile: trend systems have more small losses and fewer large profits, and mean-reverting systems have many small profits and a few large losses. While you can alter these numbers somewhat, you cannot change the big picture, nor should you, and you cannot force a market to produce a profit on demand. It’s a matter of accepting the way a system performs, and the way prices move, and working with them.

Of course, among the many trending and mean-reverting methods there are better ones. The best always have a sound premise. They are not created by scouring the computer for combinations of indicators and stop-losses. They are the results of observing the markets and understanding what makes them move.

Using trend-following as an example, we have seen that the most persistent trends are in the interest rates. That has been the result of Fed policy, effectively lowering rates over the past 25 years. Until recently many young Wall Street analysts have never seen a market where interest rates have risen. Those interest rate trends directly affect FX prices. Money flows to the countries with the highest returns net of inflation (and other political risks); therefore, lower rates create a trend towards lower currency value.

Then long-term trend-following is really trying to be on the same side of the market as government policy. It is a sound premise. On the other hand, we know why there are short-term trends – changes in supply and demand, a natural disaster, seasonality – but in most cases these trends are erratic and of unknown length. They can be profitable, but they are far less consistent than long-term trends. Based on this reasoning, many hedge funds and Commodity Trading Advisors (CTAs) have adopted macrotrends as a large part of their portfolio with great success.

One more example is pairs trading, finding two similar stocks and waiting until their prices diverge, then buying the weaker and selling the stronger. The premise is that companies in a similar business will be affected by the same factors. An earnings report in one microchip company portents similar results in other companies, with some variation based on the management of each company. Then diverging prices is seen as a temporary situation. This idea was at the root of the original high-frequency trading.

The Research and Development Process

Having decided on a method, the next step is to develop the rules for trading and controlling risk. Some of the important steps that we follow are:

More data is better. More data contain more patterns and a chance to see how the strategy works in many different conditions. Although some would say that the old data is no longer representative of that market, we don’t believe that. The market is full of uncertainty, and a system is robust only if it can deal with bull and bear markets, price shocks, and doldrums.

Apply consistent rules across all markets. We know that markets have their own personality. Apple and Amazon are not the same as a utility or Bank of America. Corn is not the same as crude oil. What makes these markets similar are the investors, the way they react to news, both macro and micro. A successful trading strategy must consider the differences, such as volatility, and the similarities, such as the trend or arbitrage, but account for them in a systematic way, using a common set of simple rules and formulas that adapt each market. The alternative is to have very specific rules for every situation and every market. Using the same rules is a robust solution. Using different rules tends to overfit the data and have little predictive value. We subscribe to the approach that “loose pants fit everyone.” The tested results don’t look as good but they have a far better chance of working.

Control the risk. Risk management is equally as important as a sound premise and a good strategy. Traders that focus their resources on a single market may reap huge returns — or huge losses. Concentration of capital increases risk. One aspect of risk control is diversification. Proper diversification should include:

Markets that are unique from one another
Multiple strategies that are unique in the way they see price movement
Equalizing risk across markets, sectors, and strategies

There is also individual trade risk. Use a strategy that takes you out of the market based a process inherent to the method rather than a stop-loss. Some traders limit risk using a rigid stop-loss order or one that varies based on volatility; however, those stops can often fight with the underlying concept, such as getting you out of a trend too soon. It is better to have a “natural” stop that conforms to the rules of the strategy. It is also possible to control risk by varying leverage, most common for portfolios of futures markets.

Finally, there is portfolio risk. We rightfully expect that daily portfolio returns, where a loss in one market may be offset by a profit in another, to be less volatile than individual stock or futures market risk; however, that doesn’t mean that the risk won’t be large during periods of stress. Prices tend to move together during a crisis. For futures, a method called “volatility stabilization” alters the leverage with the objective to keep daily volatility near a target level, often about 14%. Because stocks are not normally leveraged, portfolio risk is a combination of:

Trading equal value of each stock
Hedging with a broader index when necessary
Diversifying into unique strategies
Using a stop-loss when there is no “natural” system exit

Specific risk controls are discussed in more detail in the description of the individual strategies found on KaufmanSignals.com. For more detail and an in-depth discussion of risk, see Chapters 23 and 24 of Trading Systems and Methods, Fifth Edition (Wiley, 2013). This material is included in the reading assignments for the CMT Level II exam.

Contributor(s)

Perry J. Kaufman

Perry J. Kaufman writes extensively on markets and strategies. He began his career as a “rocket scientist,” first working on the Orbiting Astronomical Observatory (OAO-1), the predecessor of the Hubble Observatory, and then on the navigation for Gemini, later used for Apollo...

INTERMARKET ANALYSIS

Editor’s note: This article originally appeared at StockCharts.com and is republished here with permission.

Introduction

Intermarket analysis is a branch of technical analysis that examines the correlations between four major asset classes: stocks, bonds, commodities and currencies. In his classic book on Intermarket Analysis, John Murphy notes that chartists can use these relationships to identify the stage of the business cycle and improve their forecasting abilities. There are clear relationships between stocks and bonds, bonds and commodities, and commodities and the Dollar. Knowing these relationships can help chartists determine the stage of the investing cycle, select the best sectors and avoid the worst performing sectors. Much of the material for this article comes from John Murphy’s book and his postings in the Market Message at Stockcharts.com.

Inflationary Relationships

The intermarket relationships depend on the forces of inflation or deflation. In a “normal” inflationary environment, stocks and bonds are positively correlated. This means they both move in the same direction. The world was in an inflationary environment from the 1970’s to the late 1990’s. These are the key intermarket relationships in a inflationary environment:

A POSITIVE relationship between bonds and stocks
An INVERSE relationship between interest rates and stocks
Bonds usually change direction ahead of stocks
An INVERSE relationship between commodities and bonds
A POSITIVE relationship between commodities and interest rates
Commodities usually change direction after stocks
An INVERSE relationship between the US Dollar and commodities

POSITIVE: When one goes up, the other goes up also. INVERSE: When one goes up, the other goes down. Interest rates move up when bonds move down

In an inflationary environment, stocks react positively to falling interest rates (rising bond prices). Low interest rates stimulate economic activity and boost corporate profits. As interest rates fall and the economy strengthens, demand for commodities increases and commodity prices rise. Keep in mind that an “inflationary environment” does not mean runaway inflation. It simply means that the inflationary forces are stronger than the deflationary forces.

Deflationary Relationships

Murphy notes that the world shifted from an inflationary environment to a deflationary environment around 1998. It started with the collapse of the Thai Baht in the summer of 1997 and quickly spread to neighboring countries to become known as Asian currency crisis. Asian central bankers raised interest rates to support their currencies, but high interest rates choked their economies and compounded the problems. The subsequent threat of global deflation pushed money out of stocks and into bonds. Stocks fell sharply, Treasury bonds rose sharply and US interest rates decline. This marked a decoupling between stocks and bonds that would last for many years. Big deflationary events continued as the Nasdaq bubble burst in 2000, the housing bubble burst in 2006 and the financial crisis hit in 2007.

The intermarket relationships during a deflationary environment are largely the same except for one. Stocks and bonds are inversely correlated during a deflationary environment. This means stocks rise when bonds fall and vice versa. By extension, this also means that stocks have a positive relationship with interest rates. Yes, stocks and interest rates rise together.

Obviously, deflationary forces change the whole dynamic. Deflation is negative for stocks and commodities, but positive for bonds. A rise in bond prices and fall in interest rates increases the deflationary threat and this puts downward pressure on stocks. Conversely, a decline in bond prices and rise in interest rates decreases the deflationary threat and this is positive for stocks. The list below summarizes the key intermarket relationships during a deflationary environment.

An INVERSE relationship between bonds and stocks
A POSITIVE relationship between interest rates and stocks
An INVERSE relationship between commodities and bonds
A POSITIVE relationship between commodities and interest rates
A POSITIVE relationship between stocks and commodities
An INVERSE relationship between the US Dollar and commodities

Dollar and Commodities

While the Dollar and currency markets are part of intermarket analysis, the Dollar is a bit of a wild card. As far as stocks are concerned, a weak Dollar is not bearish unless accompanied by a serious advance in commodity prices. Obviously, a big advance in commodities would be bearish for bonds. By extension, a weak Dollar is also generally bearish for bonds. A weak Dollar acts an economic stimulus by making US exports more competitive. This benefits large multinational stocks that derive a large portion of their sales overseas.

What are the effects of a rising Dollar? A countries currency is a reflection of its economy and national balance sheet. Countries with strong economies and strong balance sheets have stronger currencies. Countries with weak economies and big debt burdens are subject to weaker currencies. A rising Dollar puts downward pressure on commodity prices because many commodities are priced in Dollars, such as oil. Bonds benefit from a decline in commodity prices because this reduces inflationary pressures. Stocks can also benefit from a decline in commodity prices because this reduces the costs for raw materials.

Industrial Metals and Bonds

Not all commodities are created equal. In particular, oil is prone to supply shocks. Unrest in oil producing countries or regions usually causes oil prices to surge. A price rise due to a supply shock is negative for stocks, but a price rise due to rising demand can be positive for stocks. This is also true for industrial metals, which are less susceptible to these supply shocks. As a result, chartists can watch industrial metals prices for clues on the economy and the stock market. Rising prices reflect increasing demand and a healthy economy. Falling prices reflect decreasing demand and a weak economy. The chart below shows a clear positive relationship between industrial metals and the S&P 500.

Industrial metals and bonds rise for different reasons. Metals move when the economy is growing and/or when inflationary pressures are building. Bonds decline under these circumstances and rise when the economy is weak and/or deflationary pressures are building. A ratio of the two can provide further insights into economic strength/weakness or inflation/deflation. The ratio of industrial metal prices to bond prices will rise when economic strength and inflation are prevalent. This ratio will decline when the economic weakness and deflation are dominant.
Staples/Discretionary Ratio

Chartists can also compare the performance of the consumer discretionary sector to the consumer staples sector for clues on the economy. Stocks in the consumer discretionary sector represent products that are optional.

These industry groups include apparel retailers and produces, shoe retailers and produces, restaurants and autos. Stocks in the consumer staples sector represent products that are necessary, such as soap, toothpaste, groceries, beverages and medicine. The consumer discretionary sector tends to outperform when the economy is buoyant and growing. This sector underperforms when the economy is struggling or contracting.

Chartists can compare the performance of these two with a simple ratio chart of the Consumer Discretionary SPDR (XLY) divided by the Consumer Staples SPDR (XLP). The chart above shows this ratio with the S&P 500. The ratio was rather choppy in 2004, 2005 and 2006. A strong downtrend took hold in 2007 as the consumer discretionary sector underperformed the consumer staples sector. Put another way, the consumer staples sector outperformed the consumer discretionary sector. Also notice that this ratio peaked ahead of the S&P 500 in 2007 and broke support ahead of the market. The ratio bottomed ahead of the S&P 500 in late 2008 and broke resistance as the S&P 500 surged off the March 2009 low.

Business Cycle

The graph below shows the idealized business cycle and the intermarket relationships during a normal inflationary environment. This cycle map is based on one shown in the Intermarket Review by Martin J. Pring (www.pring.com). The business cycle is shown as a sine wave. The first three stages are part of an economic contraction (weakening, bottoming, strengthening). Stage 3 shows the economy in a contraction phase, but strengthening after a bottom. As the sine wave crosses the centerline, the economy moves from contraction to the three phases of economic expansion (strengthening, topping and weakening). Stage 6 shows the
economy in an expansion phase, but weakening after a top.

Stage 1 shows the economy contracting and bonds turning up as interest rates decline. Economic weakness favors loose monetary policy and the lowering of interest rates, which is bullish for bonds.
Stage 2 marks a bottom in the economy and the stock market. Even though economic conditions have stopped deteriorating, the economy is still not at an expansion stage or actually growing. However, stocks anticipate an expansion phase by bottoming before the contraction period ends.
Stage 3 shows a vast improvement in economic conditions as the business cycle prepares to move into an expansion phase. Stocks have been rising and commodities now anticipate an expansion phase by turning up.
Stage 4 marks a period of full expansion. Both stocks and commodities are rising, but bonds turn lower because the
expansion increases inflationary pressures. Interest rates start moving higher to combat inflationary pressures.
Stage 5 marks a peak in economic growth and the stock market. Even though the expansion continues, the economy grows at a slower pace because rising interest rates and rising commodity prices take their toll. Stocks anticipate a contraction phase by peaking before the expansion actually ends. Commodities remain strong and peak after stocks.
Stage 6 marks a deterioration in the economy as the business cycle prepares to move from an expansion phase to a contraction phase. Stocks have already been moving lower and commodities now turn lower in anticipation of decreased demand from the deteriorating economy.

Keep in mind that this is the ideal business cycle in an inflationary environment. Stocks and bonds advance together in stages 2 and 3. Similarly, both decline in stages 5 and 6. This would not be the case in a deflationary environment, when bonds and stocks would move in opposite directions.

Sector Rotation

Unsurprisingly, the business cycle influences the rotation of stock market sectors and industry groups. Certain sectors perform better than others during specific phases of the business cycle. Knowing the stage of the business cycle can help investors position themselves in the right sectors and avoid the wrong sectors.

The graph above shows the economic cycle in green, the stock market cycle in red and the best performing sectors at the top. The green economic cycle corresponds to the business cycle shown above. The centerline marks the contraction/expansion threshold for the economy. Notice how the red market cycle leads the business cycle. The market turns up and crosses the centerline before the economic cycle turns. Similarly, the market turns down and crosses below the centerline ahead of the economic cycle.

Cyclicals, which is the same as the consumer discretionary sector, are the first to turn up in anticipation of a bottom in the economy. Technology stocks are not far behind. These two groups are the big leaders at the beginning of a bull run in the stock market.

The top of the market cycle is marked by relative strength in materials and energy. These sectors benefit from a rise in commodity prices and a rise in demand from an expanding economy. The tipping point for the market comes when leadership shifts from energy to consumer staples. This is a sign that commodity prices are starting to hurt the economy.

The market peak and downturn are followed by a contraction in the economy. At this stage, the Fed starts to lower interest rates and the yield curve steepens. Falling interest rates benefit debt-laden utilities and business at banks. The steepening yield curve also improves profitability at banks and encourages lending. Low interest rates and easy money eventually lead to a market bottom and the cycle repeats itself.

The two sector PerfCharts below show relative performance for the nine sector SPDRs near the 2007 peak and after the 2003 bottom. The S&P 500 peaked from July to October 2007 and broke down in the fourth quarter of that year. In the summer of 2007, the energy and materials sectors were leading the market and showing relative strength. Also notice at the consumer discretionary was lagging the S&P 500. This section action matches what is expected at a market top.

The S&P 500 bottomed in March 2003 and began a powerful bull run that lasted until the peak in the summer of 2007. The consumer discretionary and technology sectors led the first move off the March 2003 low. These two showed relative strength that affirmed the importance of the 2003 bottom.

Conclusions

Intermarket Analysis is a valuable tool for long-term or medium-term analysis. While these intermarket relationships generally work over longer periods of time, they are subject to draw-downs or periods when the relationships do not work. Big events such as the Euro crisis or the US Financial crisis can throw certain relationships out of whack for a few months. Furthermore, the tools shown in this article should be used in conjunction with other technical analysis techniques. The XLY/XLP ratio chart and the Industrial Metals/Bond Ratio chart could be part of a basket of broad market indicators designed to assess the overall strength or weakness of the stock market. One indicator or one relationship should not be used on its own to make a sweeping assessment of market conditions.

Contributor(s)

Arthur Hill, CMT

Arthur Hill, who holds the Chartered Market Technician (CMT) designation, is the Chief Technical Strategist at Trend Investor Pro. He takes a quantitative approach to trading using rule-based strategies that are tested in different market environments. Arthur has written a book defining...

INTEREST RATES AND STOCK PRICES

Editor’s note: Stan Lipstadt, Vice President of the MTA in 1976-1977, and Vice President for seminars for the MTA on multiple occasions between 1978 and 1983, died on October 30, 2013 at the age of 72.

Stan was the president and CEO of PSM Investors Inc., an investment advisory firm he founded in 1976. He first worked as securities analyst and economist at First National Bank of Chicago from 1967 to 1969. He also worked as a securities analyst with Keystone Custodian Funds from 1969 to 1972 and as an assistant vice president at Endowment Management & Research Corp. from 1972 through 1979.

The most important factor in Lipstadt’s model was the tracking of daily points up, points down, volume up and volume down, numbers collected from the Lowry Report Service, West Palm Beach, FL. Buy and sell rules were based on long-term moving averages and the system averaged three to four trades a year. Stan managed over $300 million, much of it in variable annuities.

This article originally appeared in the November 1979 MTA Journal, issue 6. Like Ralph Acampora’s 1982 Journal article and so many other articles in the archives of the Journal, it is still timely and offers useful information for technician analysts working to forecast markets years after it was written.

James D. Anderson painted an excellent broad-brush analysis of interest rates and stock market behavior (MTA Journal May 1979). The analysis to follow is more specific than Anderson’s, but covers a shorter time span.

Interest rates have fluctuated widely over time. Each generation of investors and consumers has learned to live with rates in some general area. Less attention is paid to generally “high” interest rates if that is all one has known. That is, the term “high interest rates” is a relative one, and can be determined only by what came before and comes after the interest rate level in question. Over a period of centuries rates have varied by many hundreds of multiples and have even been negative at certain times and
under certain conditions.

It has long been my premise that interest rate levels are less informative, as they apply to stock market behavior, than is the slope of the yield curve. Especially enlightening are shifts in the yield curve slope.

One measure of the slope of the yield curve is the ratio of Moody’s AAA bond yields to Treasury bill yields; that is, the ratio of long-term yields to short-term yields. Any two time-related yields can be used, but the two above have relatively continuous series, easily found in historical texts.

The first inquiry we can make concerns the level of the slope of the yield curve. The period under study is the 1,470 weeks between late 1949 and 1977. The first table below shows these computations broken into a series of “trigger points”, where levels around the 100 area indicate a time when long-term rates and short-term rates are similar and readings around, say, 140 show times when long-term rates are significantly higher than shortterm rates (a more normal yield curve).

Looking at that table, we find that, out Looking at that table, we find that, out of the 1,470 weeks under consideration, only 165 were found when long-term and short-term rates were within 10% of each other. That is, if long-term rates were 8%, then Treasury bill yields were 7.27% or higher. Or, if long-term rates were 9%, then Treasury bill yields were higher than 8.18%. This “close to inversion” condition existed for only 11% of all observations. Clearly this is a relatively rare event.

During these 165 weeks the Dow Jones Industrial Average fell at an annual rate of -21.4%.

Conversely, there were 1,305 weeks (the remainder) where the foregoing condition did not exist, where long-term yields were more than 10% greater than short-term yields. And, for those weeks the Dow Industrials rose at an average annual rate of +9.3%.

Moving up the ladder a notch, there were 263 weeks where long-term and short-term yields were within 15% of each other. During these weeks (which of course include the above case as well) the DJIA showed an annual rate of change of -11.7%. And the converse event, where long and short-term rates were more than 15% apart, corresponded to a DJIA rate of return equal to +9.5% per year.

The least restrictive trigger point covered (140%) showed the most positive DJIA results, while the most restrictive trigger point (110%) showed the largest negative results.

CONCLUSION: THE DJIA TENDS TO DO BEST WHEN THE SPREAD BETWEEN LONG-TERM AND SHORT-TERM INTEREST RATES IS LARGE, AND TENDS TO DO MOST POORLY WHEN THAT SPREAD IS VERY NARROW OR NONEXISTENT.

The results above are not terribly surprising. Most everyone who has even cursorily looked at the relationship between interest rates and stock market performance would conclude that during periods of monetary tightness, short-term rates tend to rise vis-a-vis long-term rates, and stock prices tend to be weak. And during periods of monetary ease, short-term rates tend to drop more rapidly than long-term rates (widening the spread) and stock prices tend to react favorably.

Having looked at the static slope of the yield curve through the above analysis, we can then look at the trend of the slope, by comparing its current value with some past value, say, 52 weeks prior. That is, it might be important to have some knowledge not only of where we are as regardsyield curve slope, but where we have been as well.

The second table shows the results of this analysis, and some of the results of this analysis, and some of the results are rather surprising. For example, we can divide those 165 weeks when AAA and T-bill rates were less than 10% apart into two separate groups: when the rates were less that 10% apart and the trend of these rates over 52 weeks was down (153 weeks) and when the rates were less than 10% apart and the trend over 52 weeks was up (12 weeks).

A glance to the right hand side of the table shows what a difference a trend makes. When the slope was 110% or less and the trend was down the DJIA declined at an annual rate of -18.01%. But when the slope was 110% or less and the trend was -u p the DJIA showed a rate of return of -53.88%

Similar spreads between the various trigger points can be found throughout the table. In every case, the trend of the slope was meaningful, sometimes very much so. Even at the midpoint of the data, where the slope is 120% and the number of weeks is essentially divided in two, 543 weeks vs. 510 weeks, we find in the first case a DJIA gain of 5.59%, and in the second a DJIA gain of +16.88%.

One caveat: it would be unfair to the data to draw very strong conclusions about the 12 week performance when the spread between rates was less than 10% and the trend were up (-53.88%). Those 12 weeks constitute an extremely small sample size to the total universe, and they all occur during 1974. However, the concept is clear.

Looked at from the bullish sense first, if the current AAA/T-Bill Ratio is greater than say, 125%, the DJIA has an expected annualized rate of gain equal to almost +13% (Table I). Further, if that 125% reading is higher than that seen 52 weeks earlier (that is, the trend is up) that expected annualized rate of gain rises to almost +19% (table 2).

From the bearish side, levels below 120% on the AAA/T-Bill Yield Ratio have been accompanied by DJIA annualized rates of return of about -11% (Table II). Further, if that 120% ratio is higher than that seen 52 weeks earlier the Dow Industrials’ expected annualized return drops to about -31%.

CONCLUSION: THE DJIA TENDS TO DO BEST WHEN THE RATIO OF LONGTERM TO SHORT-TERM INTEREST RATES IS HIGH AND GREATER THAN A SIMILAR COMPUTATION MADE 52 WEEKS EARLIER. THE DJIA TENDS TO DO MOST POORLY WHEN THE RATIO OF LONG-TERM TO SHORT-TERM INTEREST RATES IS LOW BUT HIGHER THAN THE READING OF A YEAR PRIOR.

What we have here is a surprise, at least to me. We can agree that, from the bullish side, falling rates are positive and, the more steeply sloped the yield curve becomes, the more bullish the configuration for stocks. But the bearish argument is fascinating. Picture, if you will, a period of tightening monetary policy resulting in a relatively flat (or inverted) yield curve. After the general peak in interest rates, and after the yield curve begins to return to a more “normal” condition, STOCKS BECOME MOST VULNERABLE TO DECLINE.

This brings us to the current situation, where we have yet to see any material improvement in the slope of the yield curve. The AAA/T-Bill Yield Ratio first dropped below 110% on September 22, 1978. It has tended to decline steadily from that point and, with only two exceptions as this is written (May 19791, has been inverted since December 22, 1978.

If interest rates do not improve materially until the fourth quarter of 1979 (and you will know that by the time you read this), the trend comparisons will be especially negative insofar as stock price performance is concerned, until the slope of the yield curve exceeds 120%. History would suggest that such a shift will take -a-t least 8-10 weeks to accomplish, and during that shift market vulnerability will be at its greatest.

There are some technicians who maintain that interest rate studies are beyond the purview of the stock market technician. However, as professional investors we must all acknowledge, sometimes grudgingly, that a relationship between the two areas has existed and may still exist. When stock prices do not appear continually accommodating to our argument we sometimes appear all too willing to ignore the data and go with the current price trend. Too many times than we care to remember this has caused major judgment errors. As this is written (May 1979) there is no evidence that any improvement in the interest rate structure is occurring. The AAA/TBill Yield Ratio remains exceedingly close to its poorest reading of the cycle. Until some improvement is seen, the trend outlook for equities remains decidedly unfavorable.

Contributor(s)

Stan Lipstadt

LONG-TERM ELLIOT WAVE ANALYSIS OF GOLD

Editor’s note: This article is presented as an example of a comprehensive approach to Elliott Wave analysis.

Main Wave Count.

Monthly Chart

My main monthly wave count expects that a grand super cycle wave completed at 1,921.15, and a grand super cycle correction began there. Within the correction the first five down is incomplete.

The parallel channel drawn about super cycle wave (V) is clearly breached by downward movement indicating this wave is over, and the next wave is underway. This is my main wave count because this fifth wave fits so nicely within its channel, and the channel is breached.

Ratios within super cycle wave (V) are: cycle wave (III) has no Fibonacci ratio to cycle wave (I), and cycle wave (V) is 21.44 short of 1.618 the length of cycle wave (III).

Ratios within cycle wave (III) are: primary wave 3 has no Fibonacci ratio to primary wave 1, and primary wave 5 is 11.09 longer than 2.618 the length of primary wave 1.

Ratios within cycle wave (V) are: primary wave 3 has no Fibonacci ratio to primary wave 1, and primary wave 5 is 18.67 longer than 0.618 the length of primary wave 3.

Within primary wave 3 within cycle wave III there are no adequate Fibonacci ratios between intermediate waves (1), (3), and (5). This lack of ratios within the middle of a third wave is unusual for Gold, and must reduce the probability that this wave count (or at least, that part of the wave count) is correct. This is why I have considered the alternate below.

Cycle wave I lasted 2 months, cycle wave III lasted 85 months (four short of a Fibonacci 89), and cycle wave V lasted 35 months (one more than a Fibonacci 34).

Weekly Chart.

Primary wave 1 must have ended at 1,532.90 in September 2011. Trying to see it as ended at 1,522.75 in December 2011 (the next low) would give it a strong three wave look. First waves must subdivide as fives, and should look like fives on a monthly chart, particularly for Gold which has the most typical looking Elliott wave structures of any market I have analysed.

Primary wave 2 begins at 1,532.90 in September, 2011 and lasts 53 weeks. The structure is a running flat: intermediate wave (C) ends just 7.08 below the end of intermediate wave (A), and intermediate wave (B) was a 102% correction of intermediate wave (A). I have checked the subdivisions of this structure on the daily chart and it fits perfectly. So although it is rare that is how it subdivides, particularly the B wave within the flat because trying to see that movement as anything other than a “three” would not fit.

Primary wave 3 is just 12.54 short of 1.618 the length of primary wave 1.

For this wave count to have the right look on a weekly chart it is most likely that primary wave 4 was not over in a mere nine weeks. It is most likely to continue further to take up more time, and may find resistance at the upper edge of the big maroon parallel channel.

There are several possible structures that primary wave 4 may complete as. I am labeling it as an A-B-C flat correction. It would most likely be an expanded flat where intermediate wave (B) within it reaches 1,168 or below. If this price point is reached then I would expect a five wave structure upwards for intermediate wave (C) to move substantially above 1,433.83.

Primary wave 4 may also be a double combination or a triangle. When this current zigzag downwards is completed I would consider at least three possibilities for the next wave upwards based upon these three different structures for primary wave 4.

It is possible that primary wave 4 is over and that primary wave 5 is underway. However, that scenario has such a low probability I do not want to chart it.

Movement below 1,032.70 would invalidate the alternate wave count below, and provide me with more confidence that this main wave count is correct.

Alternate Wave Count.

Monthly Chart.

This alternate wave count looks at the possibility that super cycle wave (V) is incomplete and that recent downward movement is a fourth wave correction within it.

Cycle wave I lasted 103 months with no Fibonacci relationship, and cycle wave III lasted 35 months (one longer than a Fibonacci 34).

Cycle wave III is 24.51 short of 1.618 the length of cycle wave I.

Within cycle wave I there are no Fibonacci ratios between primary waves 1, 3, and 5.

Ratios within cycle wave III are: primary wave 3 has no Fibonacci ratio to primary wave 1, and primary wave 5 is 18.70 longer than 0.618 the length of primary wave 3.

Ratios within primary wave 3 within cycle wave III are: intermediate wave (3) is 5.83 short of 2.618 the length of intermediate wave (1), and intermediate wave (5) is 12.14 longer than 1.618 the length of intermediate wave (3). These excellent ratios are typical for the middle of a third wave for Gold.

However, there are some problems with this wave count that reduce its probability to an alternate.

The channel drawn about this possible fifth wave of super cycle wave (V) is overshot by downward movement within this last month. I would have expected the lower edge of this channel to provide support.

The first wave upward from the low labelled cycle wave IV subdivides as a three wave structure. It could be the first wave within a leading diagonal, but because leading diagonals in first wave positions are less common than impulses this must reduce the probability of this wave count.

Movement below 1,180.40 is expected for the main wave count. If this happens then this alternate would further reduce in probability; at that stage cycle wave IV must be incomplete and only the first five down would be ending. It is difficult to see how cycle wave IV could continue further as it has very little room to move into. Cycle wave IV may not move into cycle wave I price territory. This wave count is invalidated with movement below 1,032.70.

Conclusion.

It is most likely that Gold is nearing the end of the first five wave structure downward within a multi-year correction.

When the first five down is complete then I would expect a three wave structure upwards which may not make a new all time high.

That should be followed by another five wave structure downwards to new lows.

Contributor(s)

Lara Iriarte, CMT

Lara Iriarte, CMT holds a BSc in Science from Auckland University. A science degree has taught her to view data objectively and think logically. She provides daily Elliott wave and technical analysis of the S&P500 cash and Gold spot markets to her...

A FORECAST FOR THE NIFTY

The Nifty is a benchmark index for the stock market in India. This index, along with many other global markets, reached a top in January 2008 at a high of 6357.10. On a closing basis, the Nifty made an all-time high in December 2007 when it closed at 6138.60

The bear market that followed found a low at 2252.75 in October 2008. After reaching its bottom, the Nifty consolidated for a period of four months until February 2009. The rally that began in March 2009 pushed the index back to its previous high, reaching 6338.50 in November 2010 forming a double top pattern. Double tops are a trend reversal signal.

A correction followed the double top and the Nifty pull backed to a low of 4531.15 in December 2011. This was a higher low than the previous low set in October 2008.

The Nifty has been confined to a trading range pattern since November 2007 with highs more or less close to the same levels formed in December 2008, November 2010 and the recent highs made in May 2013 at 6229.45.

On the chart, the top trend line touches all of the highs made on the Nifty and the lower, ascending trend line touches all of the higher bottoms formed from 2008 until 2013. This is a crystal clear consolidation and continuation pattern which we call an ascending triangle.

As we head towards the apex (the point where both the trend lines meet) we expect this pattern to be resolved with a breakout to the upside. The price breakout would be confirmed with a volume spike that will ultimately confirm a price-volume breakout on the Nifty. We expect this breakout to be followed by a new bull market with an initial upside target of 6700-7300 based on the pattern.

Ultimately, our upside target is 8145, about 28% above the previous all-time high of 6357 levels.

We expect this market action to unfold over the next 3-6 quarters with levels of 6700-7300-8145 being reached. A strict stop loss at 5735.30 would invalidate this signal and would be the ultimate game changer for the bull market.

CONCLUSION:

As we can see on the Nifty long-term monthly and quarterly charts, markets have spent five years in a of consolidation pattern after a huge run-up into 2008. Markets are now ready to gear up for the next bull run which we see in coming quarters when we expect equities to outperform other asset classes.

Contributor(s)

Purab Shah

Purab Shah has more than seven years of experience in FII Institutional Sales and Trading services. He is primarily focused on Indian markets but also watches other APAC markets along with developed markets around the world and other asset classes including currencies...